the efficiency of its operations and the flow of its processes are also critical factors in its success.

For these reasons Medtronic set itself the goals of assuring that it produced high-quality products while at the same time increasing efficiency and improving flow. Webster highlighted three issues that Medtronic found to be important in reaching these goals: lead time, external variability, and internal variability. Lead time is the period of time from the beginning to the end of a process. A patient who must sit in the waiting room of an emergency room for three hours is an example of a need to reduce lead time. Variability refers to differences in conditions or in how a process is performed; external variability refers to differences that cannot be controlled by the process’s operator, while internal variability refers to processes that can be. An epidemic would be an example of external variability, Webster said, while incorrect prescriptions would be an example of internal variability. If an organization can reduce lead time and internal variability, he said, it can gain the flexibility it needs to manage external variability, which in turn will lead to improved customer experiences and reduced costs. These three issues—lead time, external variability, and internal variability—are important not just in manufacturing, Webster said, but in health care as well.

There are a number of tools that can be used to improve quality and focus on the problems of lead time and variability, Webster said. In its efforts to maximize profits, Medtronic chose two: Six Sigma and Lean. In particular, Medtronic combined the two tools to create an innovative technique it called Lean Sigma. The company created Lean Sigma for three reasons, Webster said.

The first reason was that the goals of both of these tools are to decrease error and reduce waste from processes. Six Sigma focuses on the efficiency of a single process, using standard deviations as a measure to track performance. The methodology Six Sigma follows is called DMAIC, for Define, Measure, Analyze, Improve, and Control. The first step is to characterize problems with products or outcomes by defining what the problems are and then finding ways to measure performance. After measuring performance, these resulting data undergo statistical analyses to identify the problem with the process. Only when the process problem is identified can the process be improved, whether through automation or perhaps by something as simple as turning off a knob. The last step of DMAIC is control, which refers to the need to sustain change so that the problem does not recur. Statistical testing and evidence are two essential components of Six Sigma, Webster noted.

Lean also follows the DMAIC methodology, Webster explained,



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